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Emil Eirola
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2010 – 2019
- 2019
- [j6]Jonas Tana, Emil Eirola, Kristina Eriksson-Backa:
Rhythmicity of health information behaviour. Aslib J. Inf. Manag. 71(6): 773-788 (2019) - [i3]Anton Akusok, Emil Eirola:
Comparison of Classification Methods for Very High-Dimensional Data in Sparse Random Projection Representation. CoRR abs/1912.08616 (2019) - [i2]Anton Akusok, Emil Eirola, Yoan Miche, Ian Oliver, Kaj-Mikael Björk, Andrey Gritsenko, Stephen Baek, Amaury Lendasse:
Incremental ELMVIS for unsupervised learning. CoRR abs/1912.08638 (2019) - [i1]Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Amaury Lendasse:
Extreme Learning Tree. CoRR abs/1912.09087 (2019) - 2018
- [c16]Anton Akusok, Emil Eirola:
Comparison of Classification Methods for Very High-Dimensional Data in Sparse Random Projection Representation. ELM 2018: 17-26 - [c15]Renjie Hu, Venous Roshdibenam, Hans J. Johnson, Emil Eirola, Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse:
ELM-SOM: A Continuous Self-Organizing Map for Visualization. IJCNN 2018: 1-8 - 2017
- [j5]Paolo Palumbo, Luiza Sayfullina, Dmitriy Komashinskiy, Emil Eirola, Juha Karhunen:
A pragmatic android malware detection procedure. Comput. Secur. 70: 689-701 (2017) - [c14]Anton Akusok, Emil Eirola, Yoan Miché, Andrey Gritsenko, Amaury Lendasse:
Advanced query strategies for Active Learning with Extreme Learning Machines. ESANN 2017 - [c13]Andrey Gritsenko, Emil Eirola, Daniel Schupp, Edward R. Ratner, Amaury Lendasse:
Solve Classification Tasks with Probabilities. Statistically-Modeled Outputs. HAIS 2017: 293-305 - [c12]Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Yoan Miché, Hans J. Johnson, Amaury Lendasse:
Brute-force Missing Data Extreme Learning Machine for Predicting Huntington's Disease. PETRA 2017: 189-192 - 2016
- [j4]Dusan Sovilj, Emil Eirola, Yoan Miche, Kaj-Mikael Björk, Rui Nian, Anton Akusok, Amaury Lendasse:
Extreme learning machine for missing data using multiple imputations. Neurocomputing 174: 220-231 (2016) - [c11]Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Juha Karhunen:
Android Malware Detection: Building Useful Representations. ICMLA 2016: 201-206 - [c10]Kaj-Mikael Björk, Emil Eirola, Yoan Miché, Amaury Lendasse:
A new application of machine learning in health care. PETRA 2016: 49 - 2015
- [c9]Emil Eirola, Andrey Gritsenko, Anton Akusok, Kaj-Mikael Björk, Yoan Miche, Dusan Sovilj, Rui Nian, Bo He, Amaury Lendasse:
Extreme Learning Machines for Multiclass Classification: Refining Predictions with Gaussian Mixture Models. IWANN (2) 2015: 153-164 - [c8]Luiza Sayfullina, Emil Eirola, Dmitry Komashinsky, Paolo Palumbo, Yoan Miché, Amaury Lendasse, Juha Karhunen:
Efficient Detection of Zero-day Android Malware Using Normalized Bernoulli Naive Bayes. TrustCom/BigDataSE/ISPA (1) 2015: 198-205 - 2014
- [j3]Emil Eirola, Amaury Lendasse, Vincent Vandewalle, Christophe Biernacki:
Mixture of Gaussians for distance estimation with missing data. Neurocomputing 131: 32-42 (2014) - [c7]Emil Eirola, Amaury Lendasse, Juha Karhunen:
Variable selection for regression problems using Gaussian mixture models to estimate mutual information. IJCNN 2014: 1606-1613 - [c6]Emil Eirola, Amaury Lendasse, Francesco Corona, Michel Verleysen:
The delta test: The 1-NN estimator as a feature selection criterion. IJCNN 2014: 4214-4222 - 2013
- [j2]Qi Yu, Yoan Miche, Emil Eirola, Mark van Heeswijk, Eric Séverin, Amaury Lendasse:
Regularized extreme learning machine for regression with missing data. Neurocomputing 102: 45-51 (2013) - [j1]Emil Eirola, Gauthier Doquire, Michel Verleysen, Amaury Lendasse:
Distance estimation in numerical data sets with missing values. Inf. Sci. 240: 115-128 (2013) - [c5]Emil Eirola, Amaury Lendasse:
Gaussian Mixture Models for Time Series Modelling, Forecasting, and Interpolation. IDA 2013: 162-173 - [c4]Amaury Lendasse, Anton Akusok, Olli Simula, Francesco Corona, Mark van Heeswijk, Emil Eirola, Yoan Miche:
Extreme Learning Machine: A Robust Modeling Technique? Yes! IWANN (1) 2013: 17-35 - 2010
- [c3]Laura Kainulainen, Qi Yu, Yoan Miche, Emil Eirola, Eric Séverin, Amaury Lendasse:
Ensembles of Locally Linear Models: Application to Bankruptcy Prediction. DMIN 2010: 280-286 - [c2]Yoan Miche, Emil Eirola, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse, Michel Verleysen:
Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs. ESANN 2010
2000 – 2009
- 2008
- [c1]Emil Eirola, Elia Liitiäinen, Amaury Lendasse, Francesco Corona, Michel Verleysen:
Using the Delta Test for Variable Selection. ESANN 2008: 25-30
Coauthor Index
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